A Scalable Platform for Single-Snapshot Direction Of Arrival (DOA) Estimation in Massive MIMO Systems

With the development of Radio Frequency (RF) massive Multiple Inputs-Multiple Outputs (MIMO) array systems for Beyond 5G (B5G) applications, real-time DOA estimation has become challenging due to large antenna architectures producing a staggering amount of data. Traditional DOA estimation techniques are not scalable since they either require multiple snapshots of data or computationally expensive matrix operations hindering fast processing. To address these challenges, we propose a single-snapshot DOA processor based on the Alternating Direction Method of Multipliers (ADMM). The algorithm is modified to handle complex-valued measurements. We develop a High-Level Synthesis (HLS) based scalable FPGA design to handle multiple array sizes ranging from 8 to 512 elements. Our system implemented on a Xilinx Ultra96-V2 FPGA, operates at a frequency of 100 MHz with a sub-200..s processing time for a 512-antenna array, thereby meeting the millisecond-level processing time specifications of B5G applications.